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dc.contributor.authorMandal, S.
dc.contributor.authorPrabaharan, N.
dc.date.accessioned2008-07-18T05:39:01Z
dc.date.available2008-07-18T05:39:01Z
dc.date.issued2003
dc.identifier.citationSixth International Conference on Costal and Port Engineering in Developing Countries (COPEDEC VI 2003), Colombo, Sri Lanka 15th to 19th September 2003,
dc.identifier.urihttp://drs.nio.org/drs/handle/2264/1232
dc.description.abstractThis paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena. The performance of the numerical wave model depends on how best the phenomena are expressed into the numerical schemes, so that more accurate wave parameters could be estimated. There are still scopes for improving the numerical wave models. When exact input-output parameters are known for the same phenomenon, it can be well defined by the neural network. Hindcasting of ocean wave parameters using neural networks shows its potential usefulness. It is observed that the short-term wave predictions using neural networks are very close to the actual ones. Ocean wave forecasting using recurrent network yields very high correlation coefficients. The correlation coefficients for the lead of 3, 6, 12 and 24 hours are 0.95, 0.90, 0.87 and 0.73 respectively. It is also observed that the neural network simplifies not only the complex phenomena, but also predicts fairly accurate wave parameters.
dc.language.isoen
dc.publisherLanka Hydraulic Institute, Sri Lanka
dc.rightsCopyright [2003]. It is tried to respect the rights of the copyright holders to the best of the knowledge. If it is brought to our notice that the rights are violated then the item would be withdrawn.
dc.subjectwave predication
dc.subjectnumerical analysis
dc.subjectmathematical models
dc.subjectocean waves
dc.subjectcorrelation
dc.subjectwave hindcasting
dc.titleAn overview of the numerical and neural network accosts of ocean wave prediction
dc.typeConference Article


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